You're misunderstanding what I mean. Sorry, I have trouble articulating this idea. "Idea" was probably not the best word, but I'm not sure of a better one. LLM

You're misunderstanding what I mean. Sorry, I have trouble articulating this idea. "Idea" was probably not the best word, but I'm not sure of a better one. LLMs can, in effect, translate some ideas into code. Under the hood, though, they are not. They are predicting next tokens based on context. There are impressive and obviously useful emergent properties of how good they are at predicting tokens, but that is what they are doing. There's no question there. That's a fact. It's not a direct translation, however, as is the case with compiled languages. Compiled languaged directly translate the idea you communicate to them into machine/byte code in a deterministic, predictable, and importantly tractable way. LLMs do not do that. They aren't abstracting what the computer can do so that you can more effectively write instructions. as you say > It might not always be good or maintainable code What if your idea _was_ good and/or maintainable machine/byte code? What if you needed to examine the output code and ensure some quality of it. With a compiler, if you can communicate in a programming language what exactly what you want, it will _always_ produce machine/byte code that matches that. LLMs just don't do that. It's just not how statistical models work.